Classification of Chaotic Behaviors in Jerky Dynamical Systems
Tianyi Wang
Wolfram High School Summer Camp
Bentley University
175 Forest Street
Waltham, MA 02452, USA
Abstract
Differential equations are widely used to model systems that change over time, some of which exhibit chaotic behaviors. This paper proposes two new methods to classify these behaviors that are utilized by a supervised machine learning algorithm. Dissipative chaotic systems, in contrast to conservative chaotic systems, seem to follow a certain visual pattern. Also, the machine learning program written in the Wolfram Language is utilized to classify chaotic behavior with an accuracy around 99.1±1.1%.
Keywords: chaotic systems; jerky dynamics; differential equations; dynamical systems; phase space; supervised machine learning
Cite this publication as:
T. Wang, “Classification of Chaotic Behaviors in Jerky Dynamical Systems,” Complex Systems, 30(1), 2021 pp. 93–110.
https://doi.org/10.25088/ComplexSystems.30.1.93
